{"id":"W4389988181","doi":"10.7202/1092628ar","title":"Auto Insurance Reform for Canada’s Tort Provinces","year":2004,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Calgary","funders":"","keywords":"Incentive; Business; Payment; Liability; Tort; Work (physics); Limiting; Compensation (psychology); Public economics; Punitive damages; Damages; Transaction cost; Actuarial science; Finance; Economics; Microeconomics; Law; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001887379,0.0002455794,0.00048871,0.001953087,0.008790569,0.005513647,0.002022049,0.002014921,0.008761731],"category_scores_gemma":[0.008018663,0.0004627778,0.000729259,0.00194496,0.001316437,0.0007497665,0.001878918,0.001890957,0.0003910838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1265922,"about_ca_system_score_gemma":0.2314843,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9950382,"about_ca_topic_score_gemma":0.9972262,"domain_scores_codex":[0.995482,0.0002325162,0.00008054019,0.0002646549,0.001485566,0.00245477],"domain_scores_gemma":[0.9953904,0.0003918078,0.0001743316,0.0002707019,0.00231838,0.001454404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004635295,0.0003447859,0.06269076,0.0002123743,0.0001731862,0.001452405,0.00306907,0.01317437,0.0025782,0.6656387,0.1603891,0.08981354],"study_design_scores_gemma":[0.0004875059,0.0001940667,0.2403606,0.0002832793,0.0003182252,0.0003849798,0.004225896,0.02305663,0.002221716,0.02085263,0.7074239,0.0001905994],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6012779,0.004032506,0.002656599,0.05637974,0.0005963739,0.0005736828,0.004244959,0.0004013233,0.329837],"genre_scores_gemma":[0.9255585,0.0009881825,0.002162317,0.00536683,0.0001041098,0.00008359466,0.0008398538,0.00003866751,0.06485789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1265922,"threshold_uncertainty_score":0.9184949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02991715265544547,"score_gpt":0.2361038780600701,"score_spread":0.2061867254046247,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}